Predicting blood flow near hepatic tumors with ultrasound to improve RF ablations

描述（由申请人提供）：[目的：拟定研究旨在提高射频（RF）消融的肝癌肿瘤根除率，并增加候选患者数量。对于小于3cm的原发性或继发性恶性肝脏肿瘤患者，使用射频（RF）消融治疗的局部肿瘤根除率超过83%;不幸的是，大多数患者的肿瘤大于3cm。由于不同患者之间甚至同一患者内射频器械造成的热损伤大小存在不可预测的变化，较大肿瘤局部肿瘤根除的成功率福尔斯降至50%以下。成功率受到局部血流带走治疗期间施加的热量的限制，这可能导致一些肿瘤细胞无法达到55 ℃的细胞死亡温度以及疾病的不希望的持续和传播。目的提出一种利用三维超声图像定量测量肿瘤周围感兴趣区域（ROI）内血流的新方法。血流信息将作为射频消融器械性能的预测因子进行评估，供临床医生在消融计划期间使用，以确保所有肿瘤细胞均被破坏，并且最少量的健康组织受到干扰（对于患有严重肿瘤的患者至关重要）。 肝硬化）。方法开发基于软件的算法，从三维超声图像中重建患者特定的肝脏血管几何形状。来自患者血管内的相关多普勒颜色/速度数据将与角度校正的血管几何结构相结合，以在临床医生围绕肿瘤设置的ROI内建立“血流影响指数”。该指数将提供局部血流的量和方向的指示。将使用已知几何结构的解剖学正确肝血流模型在正常和病理流速范围内验证算法功能。将通过对废弃牛肝脏进行计划和试验消融并比较计划和实际消融尺寸来确认算法的预测能力。]

DESCRIPTION (provided by applicant): [Aim The proposed research is intended to increase the liver cancer tumor eradication rate of Radiofrequency (RF) ablation and increase the number of candidate patients. Relevance The local tumor eradication rate for patients with primary or secondary malignant liver tumors smaller than 3cm who are treated using Radiofrequency (RF) ablation is over 83%; unfortunately, the majority of patients have tumors larger than 3cm. The success rate of local tumor eradication of larger tumors falls to less than 50% due to unpredictable variation in the size of the thermal injury created by RF devices between different patients and even within the same patient. The success rates are limited by local blood flow carrying away the heat applied during treatment which can result in some tumor cells not reaching the cell death temperature of 55¿C and an undesired continuation and propagation of the disease. Objective The proposed research develops a new method of quantifying the amount of blood flow within a Region of Interest (ROI) surrounding a tumor using 3D ultrasound imagery. The flow information will be evaluated as a predictor of RF ablation device performance for use by clinicians during ablation planning to ensure that all of the tumor cells are destroyed and a minimal amount of healthy tissue is disturbed (critical for patients with cirrhosis). Methods Software based algorithms will be developed to reconstruct patient specific liver vessel geometry from 3D ultrasound Imagery. The associated Doppler color/velocity data from within the patient vessels will be combined with angle corrected vessel geometry to establish a "Flow Influence Index" within the ROI set around the tumor by the clinician. The index will provide an indication of the amount and direction of local blood flow. The algorithm function will be verified with an anatomically correct liver flow model of known geometry over a range of normal and pathological flow rates. The predictive capability of the algorithms will be validated by planning and performing test ablations on discarded cattle livers and comparing the planned and actual ablation sizes.]